How to create rank column in Python based on other columns

I have a python dataframe that looks like the following:

This dataframe has been sorted in descending order by 'transaction_count'. I want to create another column in that dataframe called 'rank' that contains the count of occurrences of cust_ID. My desired output would look something like the following:

For cust_ID = 1234 with transaction_count = 4, the rank would be 1, for the next appearance of cust_ID = 1234, the rank would be 2 and so on.

I tried the following among other things:

df['rank'] = df["cust_ID"].value_counts()
df.head(10)

But the rank column gets created as all NaN values

Any suggestions on how to approach this would be greatly appreciated!

Use groupby + cumcount:

df['rank'] = df.groupby('cust_ID').cumcount() + 1
print(df['rank'])

Output

0    1
1    2
2    1
3    1
4    2
5    3
Name: rank, dtype: int64